Evaluation of macro and micronutrient elements content from soft drinks using principal component analysis and Kohonen self-organizing maps.

This study approaches the determination of nine elements from Brazilian carbonated soft drinks of several flavors and manufactures using inductively coupled plasma optical emission spectrometry (ICP OES). The concentrations of the elements varied as follows: (in µg L-1: Cu: 4.00-78.0; Fe: 74.0-506; Mn: 20.0-66.0; Zn: 104-584) and (in mg L-1: Ca: 4.81-16.2; K: 6.73-260; Na: 26.0-175; S: 1.43-5.41; P: 0.186-219). Principal component analysis has shown some tendencies to form two groups according to the drink flavor (orange and cola), but only cola presented a clear and complete separation. Using Kohonen maps, it was observed a tendency to form three flavor groups: (i) cola, (ii) orange and lemon, and (iii) guarana. However, this last tool proved to be more accurate in the groups' formation.

[1]  Simon Haykin,et al.  Neural Networks and Learning Machines , 2010 .

[2]  F. Hu,et al.  Intake of sugar-sweetened beverages and weight gain: a systematic review. , 2006, The American journal of clinical nutrition.

[3]  D. Kara,et al.  Determination and chemometric evaluation of total aflatoxin, aflatoxin B1, ochratoxin A and heavy metals content in corn flours from Turkey. , 2014, Food chemistry.

[4]  Jean-Luc Giraudel,et al.  Characterization of strawberry varieties by SPME–GC–MS and Kohonen self-organizing map , 2006 .

[5]  Martin Šala,et al.  Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia. , 2014, Food chemistry.

[6]  Jean-Luc Giraudel,et al.  Determination of volatile characteristics of Greek and Turkish pine honey samples and their classification by using Kohonen self organising maps , 2007 .

[7]  João Aires-de-Sousa,et al.  Geographical classification of crude oils by Kohonen self-organizing maps , 2006 .

[8]  J. Tadakamadla,et al.  Enamel solubility potential of commercially available soft drinks and fruit juices in Saudi Arabia , 2015 .

[9]  M. Behpour,et al.  Simultaneous determination of Sunset yellow and Tartrazine in soft drinks using gold nanoparticles carbon paste electrode. , 2012, Food chemistry.

[10]  Principal component analysis for the forensic discrimination of black inkjet inks based on the Vis-NIR fibre optics reflection spectra. , 2015, Forensic science international.

[11]  M. P. Gómez-Carracedo,et al.  Differentiation of weathered oils using infrared indexes and self-organizing maps , 2015 .

[12]  B. Li,et al.  Profiling of anthocyanins from blueberries produced in China using HPLC-DAD-MS and exploratory analysis by principal component analysis , 2016 .

[13]  Dragos Horvath,et al.  Using self-organizing maps to accelerate similarity search. , 2012, Bioorganic & medicinal chemistry.

[14]  M. Farag,et al.  Metabolome based volatiles profiling in 13 date palm fruit varieties from Egypt via SPME GC-MS and chemometrics. , 2017, Food chemistry.

[15]  R. Heaney,et al.  Carbonated beverages and urinary calcium excretion. , 2001, The American journal of clinical nutrition.

[16]  M. Kompany‐Zareh,et al.  Application of supervised Kohonen map and counter propagation neural network for classification of nucleic acid structures based on their circular dichroism spectra. , 2014, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[17]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[18]  B. Francisco,et al.  Determination of metals in soft drinks packed in different materials by ETAAS. , 2015, Food chemistry.

[19]  Stefan Tsakovski,et al.  Surface water quality assessment using self-organizing maps and Hasse diagram technique , 2012 .

[20]  Jéssica R. P. Ribeiro,et al.  Screening of Passiflora L. mineral content using principal component analysis and Kohonen self-organizing maps. , 2017, Food chemistry.

[21]  E. Grifoni,et al.  Comparison of brass alloys composition by laser-induced breakdown spectroscopy and self-organizing maps , 2015 .

[22]  Peter Filzmoser,et al.  Effects of supervised Self Organising Maps parameters on classification performance. , 2013, Analytica chimica acta.

[23]  Donald W. Bouldin,et al.  A Cluster Separation Measure , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Federico Marini,et al.  Artificial neural networks in foodstuff analyses: Trends and perspectives A review. , 2009, Analytica chimica acta.

[25]  T. Kohonen.  Self-organized formation of topographically correct feature maps , 1982 .

[26]  O. Lee,et al.  Identifying method validation and measurement uncertainty of brominated vegetable oil in soft drinks and carbonated waters commonly consumed in South Korea. , 2018, Food chemistry.

[27]  Jaime S. Mandlate,et al.  Determination of cadmium and lead at sub-ppt level in soft drinks: An efficient combination between dispersive liquid-liquid microextraction and graphite furnace atomic absorption spectrometry. , 2017, Food chemistry.

[28]  M. Nsangou,et al.  Fluorescence Spectroscopy Combined with Chemometrics for the Investigation of the Adulteration of Essential Oils , 2017, Food Analytical Methods.

[29]  W. B. Neto,et al.  Exploratory analysis and inductively coupled plasma optical emission spectrometry (ICP OES) applied in the determination of metals in soft drinks. , 2009 .

[30]  I. S. Scarminio,et al.  Principal component analysis and hierarchical cluster analysis for homogeneity evaluation during the preparation of a wheat flour laboratory reference material for inorganic analysis , 2010 .

[31]  C. Dogan,et al.  Detection of l-Cysteine in wheat flour by Raman microspectroscopy combined chemometrics of HCA and PCA. , 2017, Food Chemistry.

[32]  T. Kohonen,et al.  Self-organizing semantic maps , 1989, Biological Cybernetics.

[33]  Francisco Azuaje,et al.  Cluster validation techniques for genome expression data , 2003, Signal Process..